Mahdi Abavisani

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Many practical applications in image processing and computer vision require one to analyze and process high-dimensional data. It has been observed that these high-dimensional data can be represented by a lowdimensional subspace. As a result, the collection of data from different classes can be viewed as samples from a union of low-dimensional subspaces. In(More)
Many research works have been done in face recognition during the last years that indicates the importance of face recognition systems in many applications including identity authentication. In this paper we propose an approach for face recognition which is suitable for unconstrained image acquisition and has a low computational cost. Since in practical(More)
This paper presents a novel approach for detection and estimation of fundamental parameters of linear frequency modulation (LFM) signals, i.e., the initial frequency and Chirp rate. The proposed approach is based on sparse representation of noisy input signals over two specific dictionaries, each designed for finding a parameter of LFM signal. Moreover, an(More)
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